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    Data assimilation using Bayesian filters and B-spline geological models

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    Type
    Conference Paper
    Authors
    Duan, Lian
    Farmer, Chris
    Hoteit, Ibrahim cc
    Luo, Xiaodong
    Moroz, Irene
    KAUST Department
    Physical Sciences and Engineering (PSE) Division
    Date
    2011-04-01
    Permanent link to this record
    http://hdl.handle.net/10754/554389
    
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    Abstract
    This paper proposes a new approach to problems of data assimilation, also known as history matching, of oilfield production data by adjustment of the location and sharpness of patterns of geological facies. Traditionally, this problem has been addressed using gradient based approaches with a level set parameterization of the geology. Gradient-based methods are robust, but computationally demanding with real-world reservoir problems and insufficient for reservoir management uncertainty assessment. Recently, the ensemble filter approach has been used to tackle this problem because of its high efficiency from the standpoint of implementation, computational cost, and performance. Incorporation of level set parameterization in this approach could further deal with the lack of differentiability with respect to facies type, but its practical implementation is based on some assumptions that are not easily satisfied in real problems. In this work, we propose to describe the geometry of the permeability field using B-spline curves. This transforms history matching of the discrete facies type to the estimation of continuous B-spline control points. As filtering scheme, we use the ensemble square-root filter (EnSRF). The efficacy of the EnSRF with the B-spline parameterization is investigated through three numerical experiments, in which the reservoir contains a curved channel, a disconnected channel or a 2-dimensional closed feature. It is found that the application of the proposed method to the problem of adjusting facies edges to match production data is relatively straightforward and provides statistical estimates of the distribution of geological facies and of the state of the reservoir.
    Citation
    Data assimilation using Bayesian filters and B-spline geological models 2011, 290:012004 Journal of Physics: Conference Series
    Publisher
    IOP Publishing
    Journal
    Journal of Physics: Conference Series
    Conference/Event name
    5th International Conference on Inverse Problems 2010
    ISSN
    1742-6596
    DOI
    10.1088/1742-6596/290/1/012004
    Additional Links
    http://stacks.iop.org/1742-6596/290/i=1/a=012004?key=crossref.71e007cb63920e4d70746a5730022d3a
    ae974a485f413a2113503eed53cd6c53
    10.1088/1742-6596/290/1/012004
    Scopus Count
    Collections
    Conference Papers; Physical Sciences and Engineering (PSE) Division; Physical Sciences and Engineering (PSE) Division

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